
"""simple docstring"""






import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_torch_available, is_vision_available


if is_torch_available():
					import torch


if is_vision_available():
					from PIL import Image

					from transformers import MgpstrProcessor, ViTImageProcessor



@require_torch
@require_vision
class 			lowercase					( unittest.TestCase		):
			lowercase        =     ViTImageProcessor if is_vision_available() else None






			@property
			def 					UpperCAmelCase							(self  :	List[str]			)       ->	Tuple:





				"""simple docstring"""


				return self.image_processor_tester.prepare_image_processor_dict()






			def 					UpperCAmelCase							(self  :	Any			)       ->	List[str]:





				"""simple docstring"""


				lowerCAmelCase												=  (3, 32, 128)
				lowerCAmelCase												=  tempfile.mkdtemp()

				# fmt: off
				lowerCAmelCase												=  ['''[GO]''', '''[s]''', '''0''', '''1''', '''2''', '''3''', '''4''', '''5''', '''6''', '''7''', '''8''', '''9''', '''a''', '''b''', '''c''', '''d''', '''e''', '''f''', '''g''', '''h''', '''i''', '''j''', '''k''', '''l''', '''m''', '''n''', '''o''', '''p''', '''q''', '''r''', '''s''', '''t''', '''u''', '''v''', '''w''', '''x''', '''y''', '''z''']
				# fmt: on
				lowerCAmelCase												=  dict(zip(SCREAMING_SNAKE_CASE_      ,range(len(SCREAMING_SNAKE_CASE_			)			)			)			)

				lowerCAmelCase												=  os.path.join(self.tmpdirname      ,VOCAB_FILES_NAMES['''vocab_file''']			)
				with open(self.vocab_file      ,'''w'''      ,encoding='''utf-8'''			) as fp:
					fp.write(json.dumps(SCREAMING_SNAKE_CASE_			) + '''\n'''			)

				lowerCAmelCase												=  {
				    '''do_normalize''': False,
				    '''do_resize''': True,
				    '''image_processor_type''': '''ViTImageProcessor''',
				    '''resample''': 3,
				    '''size''': {'''height''': 32, '''width''': 128},
				}
				lowerCAmelCase												=  os.path.join(self.tmpdirname      ,SCREAMING_SNAKE_CASE_			)
				with open(self.image_processor_file      ,'''w'''      ,encoding='''utf-8'''			) as fp:
					json.dump(SCREAMING_SNAKE_CASE_      ,SCREAMING_SNAKE_CASE_			)






			def 					UpperCAmelCase							(self  :	Dict      ,**SCREAMING_SNAKE_CASE_  :	Optional[int]			)       ->	Tuple:





				"""simple docstring"""


				return MgpstrTokenizer.from_pretrained(self.tmpdirname      ,**SCREAMING_SNAKE_CASE_			)






			def 					UpperCAmelCase							(self  :	str      ,**SCREAMING_SNAKE_CASE_  :	Optional[Any]			)       ->	str:





				"""simple docstring"""


				return ViTImageProcessor.from_pretrained(self.tmpdirname      ,**SCREAMING_SNAKE_CASE_			)






			def 					UpperCAmelCase							(self  :	Any			)       ->	Dict:





				"""simple docstring"""


				shutil.rmtree(self.tmpdirname			)






			def 					UpperCAmelCase							(self  :	str			)       ->	Dict:





				"""simple docstring"""


				lowerCAmelCase												=  np.random.randint(255      ,size=(3, 30, 400)      ,dtype=np.uinta			)

				lowerCAmelCase												=  Image.fromarray(np.moveaxis(SCREAMING_SNAKE_CASE_      ,0      ,-1			)			)

				return image_input






			def 					UpperCAmelCase							(self  :	Union[str, Any]			)       ->	List[str]:





				"""simple docstring"""


				lowerCAmelCase												=  self.get_tokenizer()
				lowerCAmelCase												=  self.get_image_processor()

				lowerCAmelCase												=  MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE_      ,image_processor=SCREAMING_SNAKE_CASE_			)
				processor.save_pretrained(self.tmpdirname			)
				lowerCAmelCase												=  MgpstrProcessor.from_pretrained(self.tmpdirname      ,use_fast=SCREAMING_SNAKE_CASE_			)

				self.assertEqual(processor.char_tokenizer.get_vocab()      ,tokenizer.get_vocab()			)
				self.assertIsInstance(processor.char_tokenizer      ,SCREAMING_SNAKE_CASE_			)

				self.assertEqual(processor.image_processor.to_json_string()      ,image_processor.to_json_string()			)
				self.assertIsInstance(processor.image_processor      ,SCREAMING_SNAKE_CASE_			)






			def 					UpperCAmelCase							(self  :	str			)       ->	int:





				"""simple docstring"""


				lowerCAmelCase												=  self.get_tokenizer()
				lowerCAmelCase												=  self.get_image_processor()

				lowerCAmelCase												=  MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE_      ,image_processor=SCREAMING_SNAKE_CASE_			)
				processor.save_pretrained(self.tmpdirname			)

				lowerCAmelCase												=  self.get_tokenizer(bos_token='''(BOS)'''      ,eos_token='''(EOS)'''			)
				lowerCAmelCase												=  self.get_image_processor(do_normalize=SCREAMING_SNAKE_CASE_      ,padding_value=1.0			)

				lowerCAmelCase												=  MgpstrProcessor.from_pretrained(
				    self.tmpdirname      ,bos_token='''(BOS)'''      ,eos_token='''(EOS)'''      ,do_normalize=SCREAMING_SNAKE_CASE_      ,padding_value=1.0			)

				self.assertEqual(processor.char_tokenizer.get_vocab()      ,tokenizer_add_kwargs.get_vocab()			)
				self.assertIsInstance(processor.char_tokenizer      ,SCREAMING_SNAKE_CASE_			)

				self.assertEqual(processor.image_processor.to_json_string()      ,image_processor_add_kwargs.to_json_string()			)
				self.assertIsInstance(processor.image_processor      ,SCREAMING_SNAKE_CASE_			)






			def 					UpperCAmelCase							(self  :	str			)       ->	Any:





				"""simple docstring"""


				lowerCAmelCase												=  self.get_image_processor()
				lowerCAmelCase												=  self.get_tokenizer()

				lowerCAmelCase												=  MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE_      ,image_processor=SCREAMING_SNAKE_CASE_			)

				lowerCAmelCase												=  self.prepare_image_inputs()

				lowerCAmelCase												=  image_processor(SCREAMING_SNAKE_CASE_      ,return_tensors='''np'''			)
				lowerCAmelCase												=  processor(images=SCREAMING_SNAKE_CASE_      ,return_tensors='''np'''			)

				for key in input_image_proc.keys():
					self.assertAlmostEqual(input_image_proc[key].sum()      ,input_processor[key].sum()      ,delta=1e-2			)






			def 					UpperCAmelCase							(self  :	Optional[int]			)       ->	List[str]:





				"""simple docstring"""


				lowerCAmelCase												=  self.get_image_processor()
				lowerCAmelCase												=  self.get_tokenizer()

				lowerCAmelCase												=  MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE_      ,image_processor=SCREAMING_SNAKE_CASE_			)

				lowerCAmelCase												=  '''test'''

				lowerCAmelCase												=  processor(text=SCREAMING_SNAKE_CASE_			)

				lowerCAmelCase												=  tokenizer(SCREAMING_SNAKE_CASE_			)
				for key in encoded_tok.keys():
					self.assertListEqual(encoded_tok[key]      ,encoded_processor[key]			)






			def 					UpperCAmelCase							(self  :	Dict			)       ->	Union[str, Any]:





				"""simple docstring"""


				lowerCAmelCase												=  self.get_image_processor()
				lowerCAmelCase												=  self.get_tokenizer()

				lowerCAmelCase												=  MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE_      ,image_processor=SCREAMING_SNAKE_CASE_			)

				lowerCAmelCase												=  '''test'''
				lowerCAmelCase												=  self.prepare_image_inputs()

				lowerCAmelCase												=  processor(text=SCREAMING_SNAKE_CASE_      ,images=SCREAMING_SNAKE_CASE_			)

				self.assertListEqual(list(inputs.keys()			)      ,['''pixel_values''', '''labels''']			)

				# test if it raises when no input is passed
				with pytest.raises(SCREAMING_SNAKE_CASE_			):
					processor()






			def 					UpperCAmelCase							(self  :	Any			)       ->	Any:





				"""simple docstring"""


				lowerCAmelCase												=  self.get_image_processor()
				lowerCAmelCase												=  self.get_tokenizer()

				lowerCAmelCase												=  MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE_      ,image_processor=SCREAMING_SNAKE_CASE_			)

				lowerCAmelCase												=  [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9], [3, 4, 3, 1, 1, 8, 9]]

				lowerCAmelCase												=  processor.char_decode(SCREAMING_SNAKE_CASE_			)
				lowerCAmelCase												=  tokenizer.batch_decode(SCREAMING_SNAKE_CASE_			)
				lowerCAmelCase												=  [seq.replace(''' '''      ,''''''			) for seq in decoded_tok]

				self.assertListEqual(SCREAMING_SNAKE_CASE_      ,SCREAMING_SNAKE_CASE_			)






			def 					UpperCAmelCase							(self  :	str			)       ->	Optional[int]:





				"""simple docstring"""


				lowerCAmelCase												=  self.get_image_processor()
				lowerCAmelCase												=  self.get_tokenizer()

				lowerCAmelCase												=  MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE_      ,image_processor=SCREAMING_SNAKE_CASE_			)

				lowerCAmelCase												=  None
				lowerCAmelCase												=  self.prepare_image_inputs()

				lowerCAmelCase												=  processor(text=SCREAMING_SNAKE_CASE_      ,images=SCREAMING_SNAKE_CASE_			)

				self.assertListEqual(list(inputs.keys()			)      ,processor.model_input_names			)






			def 					UpperCAmelCase							(self  :	Any			)       ->	int:





				"""simple docstring"""


				lowerCAmelCase												=  self.get_image_processor()
				lowerCAmelCase												=  self.get_tokenizer()

				lowerCAmelCase												=  MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE_      ,image_processor=SCREAMING_SNAKE_CASE_			)

				lowerCAmelCase												=  torch.randn(1      ,27      ,38			)
				lowerCAmelCase												=  torch.randn(1      ,27      ,50_257			)
				lowerCAmelCase												=  torch.randn(1      ,27      ,30_522			)

				lowerCAmelCase												=  processor.batch_decode([char_input, bpe_input, wp_input]			)

				self.assertListEqual(list(results.keys()			)      ,['''generated_text''', '''scores''', '''char_preds''', '''bpe_preds''', '''wp_preds''']			)




"""simple docstring"""






UpperCAmelCase        =				8.3_144_598




def __magic_name__	(				_lowerCamelCase:		float,					_lowerCamelCase:		float			)					->						float:

	'''simple docstring'''




	if temperature < 0:
		raise Exception('''Temperature cannot be less than 0 K'''			)
	if molar_mass <= 0:
		raise Exception('''Molar mass cannot be less than or equal to 0 kg/mol'''			)
	else:
		return (3 * UNIVERSAL_GAS_CONSTANT * temperature / molar_mass) ** 0.5


if __name__ == "__main__":
					import doctest

					# run doctest
					doctest.testmod()

					# example
					UpperCAmelCase        =				3_0_0
					UpperCAmelCase        =				2_8
					UpperCAmelCase        =				rms_speed_of_molecule(temperature, molar_mass)
					print(f"""Vrms of Nitrogen gas at 300 K is {vrms} m/s""")


